Notes

1
Notes
2
Simplifications of Elasticity
3
Rotated Linear Elements

• Green strain is quadratic - not so nice
• Cauchy strain cant handle big rotations
• So instead, for each element factor deformation
  gradient A into a rotation Q times a deformation
  F AQF
• Polar Decomposition
• Strain is now just F-I, compute stress, rotate
  forces back with QT
• See Mueller et al, Interactive Virtual
  Materials, GI04
• Quick and dirty version use QR, Fsymmetric part
  of R

4
Inverted Elements

• Too much external force will crush a mesh, cause
  elements to invert
• Usual definitions of strain cant handle this
• Instead can take SVD of A, flip smallest singular
  value if we have inversion
• Strain is just diagonal now
• See Irving et al., Invertible FEM, SCA04

5
Embedded Geometry

• Common technique simulation geometry isnt as
  detailed as rendered geometry
• E.g. simulate cloth with a coarse mesh, but
  render smooth splines from it
• Can take this further embedded geometry
• Simulate deformable object dynamics with simple
  coarse mesh
• Embed more detailed geometry inside the mesh for
  collision processing
• Fast, looks good, avoids the need for complex
  (and finnicky) mesh generation
• See e.g. Skeletal Animation of Deformable
  Characters," Popovic et al., SIGGRAPH02

6
Quasi-Static Motion

• Assume inertia is unimportant---given any applied
  force, deformable object almost instantly comes
  to rest
• Then we are quasi-static solve for current
  position where FinternalFexternal0
• For linear elasticity, this is just a linear
  system
• Potentially very fast, no need for time stepping
  etc.
• Schur complement technique assume external
  forces never applied to interior nodes, then can
  eliminate them from the equationJust left with
  a small system of equations for surface nodes
  (i.e. just the ones we actually can see)

7
Boundary Element Method

• For quasi-static linear elasticity and a
  homogeneous material, can set up PDE to eliminate
  interior unknowns---before discretization
• Very accurate and efficient!
• Essentially the limit of the Schur complement
  approach
• See James Pai, ArtDefo, SIGGRAPH99
• For interactive rates, can actually do more
  preinvert BEM stiffness matrix
• Need to be smart about updating inverse when
  boundary conditions change

8
Modal Dynamics

• See Pentland and Williams, Good Vibrations,
  SIGGRAPH89
• Again assume linear elasticity
• Equation of motion is MaDvKxFexternal
• M, K, and D are constant matrices
• M is the mass matrix (often diagonal)
• K is the stiffness matrix
• D is the damping matrix assume a multiple of K
• This a large system of coupled ODEs now
• We can solve eigen problem to diagonalize and
  decouple into scalar ODEs
• M and K are symmetric, so no problems here -
  complete orthogonal basis of real eigenvectors

9
Eigenstuff

• Say U(u1 u2 u3n) is a matrix with the
  columns the eigenvectors of M-1K (also M-1D)
• M-1Kui?iui and M-1Dui?iui
• Assume ?i are increasing
• We know ?1?60 and ?1?60(with u1, , u6
  the rigid body modes)
• The rest are the deformation modes the larger
  that ?i is, the smaller scale the mode is
• Change equation of motion to this basis

10
Decoupling into modes

• Take yUTx (so xUy) - decompose positions (and
  velocities, accelerations) into a sum of modes
• Multiply by UT to decompose equations into modal
  components
• So now we have 3n independent ODEs
• If Fext is constant over the time step, can even
  write down exact formula for each

11
Examining modes

• Mode i
• Rigid body modes have zero eigenvalues, so just
  depend on force
• Roughly speaking, rigid translations will take
  average of force, rigid rotations will take
  cross-product of force with positions (torque)
• Better to handle these as rigid body
• The large eigenvalues (large i) have small length
  scale, oscillate (or damp) very fast
• Visually irrelevant
• Left with small eigenvalues being important

12
Throw out high frequencies

• Only track a few low-frequency modes (5-10)
• Time integration is blazingly fast!
• Essentially reduced the degrees of freedom from
  thousands or millions down to 10 or so
• But keeping full geometry, just like embedded
  element approach
• Collision impulses need to be decomposed into
  modes just like external forces

13
Simplifying eigenproblem

• Low frequency modes not affected much by high
  frequency geometry
• And visually, difficult for observers to quantify
  if a mode is actually accurate
• So we can use a very coarse mesh to get the
  modes, or even analytic solutions for a block of
  comparable mass distribution
• Or use a Rayleigh-Ritz approximation to the
  eigensystem (eigen-version of Galerkin FEM)
• E.g. assume low frequency modes are made up of
  affine and quadratic deformations
• Do FEM, get eigenvectors to combine them

14
More savings

• External forces (other than gravity, which is in
  the rigid body modes) rarely applied to interior,
  and we rarely see the interior deformation
• So just compute and store the boundary particles
• E.g. see James and Pai, DyRT, SIGGRAPH02 --
  did this in graphics hardware!

15
Inelasticity Plasticity Fracture
16
Plasticity Fracture

• If material deforms too much, becomes permanently
  deformed plasticity
• Yield condition when permanent deformation
  starts happening (if stress is large enough)
• Elastic strain deformation that can disappear in
  the absence of applied force
• Plastic strain permanent deformation accumulated
  since initial state
• Total strain total deformation since initial
  state
• Plastic flow when yield condition is met, how
  elastic strain is converted into plastic strain
• Fracture if material deforms too much, breaks
• Fracture condition if stress is large enough

17
For springs (1D)

• Go back to Terzopoulos and Fleischer
• Plasticity change the rest length if the stress
  (tension) is too high
• Maybe different yielding for compression and
  tension
• Work hardening make the yield condition more
  stringent as material plastically flows
• Creep let rest length settle towards current
  length at a given rate
• Fracture break the spring if the stress is too
  high
• Without plasticity brittle
• With plasticity first ductile

18
Fracturing meshes (1D)

• Breaking springs leads to volume loss material
  disappears
• Solutions
• Break at the nodes instead (look at average
  tension around a node instead of on a spring)
• Note recompute mass of copied node
• Cut the spring in half, insert new nodes
• Note could cause CFL problems
• Virtual node algorithm
• Embed fractured geometry, copy the spring (see
  Molino et al. A Virtual Node Algorithm
  SIGGRAPH04)

19
Multi-Dimensional Plasticity

• Simplest model total strain is sum of elastic
  and plastic parts ??e ?p
• Stress only depends on elastic part(so rest
  state includes plastic strain)??(?e)
• If ? is too big, we yield, and transfer some of
  ?e into ?p so that ? is acceptably small

20
Multi-Dimensional Yield criteria

• Lots of complicated stuff happens when materials
  yield
• Metals dislocations moving around
• Polymers molecules sliding against each other
• Etc.
• Difficult to characterize exactly when plasticity
  (yielding) starts
• Work hardening etc. mean it changes all the time
  too
• Approximations needed
• Big two Tresca and Von Mises

21
Yielding

• First note that shear stress is the important
  quantity
• Materials (almost) never can permanently change
  their volume
• Plasticity should ignore volume-changing stress
• So make sure that if we add kI to ? it doesnt
  change yield condition

22
Tresca yield criterion

• This is the simplest description
• Change basis to diagonalize ?
• Look at normal stresses (i.e. the eigenvalues of
  ?)
• No yield if ?max-?min ?Y
• Tends to be conservative (rarely predicts
  yielding when it shouldnt happen)
• But, not so accurate for some stress states
• Doesnt depend on middle normal stress at all
• Big problem (mathematically) not smooth

23
Von Mises yield criterion

• If the stress has been diagonalized
• More generally
• This is the same thing as the Frobenius norm of
  the deviatoric part of stress
• i.e. after subtracting off volume-changing part